引用本文: 黄博华, 武芳, 许俊奎, 翟仁健, 巩现勇. 一种面向同名线要素的距离度量方法[J]. 武汉大学学报 ( 信息科学版), 2017, 42(3): 395-401.
HUANG Bohua, WU Fang, XU Junkui, ZHAI Renjian, GONG Xianyong. A Method of Distance Measurement for Corresponding Linear Feature[J]. Geomatics and Information Science of Wuhan University, 2017, 42(3): 395-401.
 Citation: HUANG Bohua, WU Fang, XU Junkui, ZHAI Renjian, GONG Xianyong. A Method of Distance Measurement for Corresponding Linear Feature[J]. Geomatics and Information Science of Wuhan University, 2017, 42(3): 395-401.

## A Method of Distance Measurement for Corresponding Linear Feature

• 摘要: 针对已有距离度量方法在表达同名线要素空间位置差异准确性方面的不足，提出了一种面向同名线要素的距离度量方法。该方法结合Hausdorff距离和Fréchet距离的特点，首先分别将同名线要素上每个顶点在对应线上的对应点内插到对应线上，利用一阶差分的方法剔除其中的粗差点，并采用中位点进行了修正，然后依序计算每个点与对应线上点的最小欧氏距离，最后取其平均值作为最终的距离值。为了验证本方法的有效性，提出了衡量距离度量方法稳定性的平均振幅（F）和准确性的准确率（R）两个评价指标。通过与欧氏距离、Hausdorff距离和Fréchet距离实验结果的对比分析，表明本方法的距离度量结果比较符合人类的认知特点，具有一定的实用性。

Abstract: In view of the current distance measurement methods in expressing the spatial location differences accuracy and deficiency of corresponding linear feature, this paper proposes a method of distance measurement for corresponding linear feature. The method combines the advantages of both hausdorff distance and fréchet distance. Firstly, the corresponding point of vertexes were interpolated into the corresponding linear. Secondly, the gross error points were eliminated by the use of first order differential and fixed it by the use of median point. Thirdly, the minimum Euclidean distance between vertexe and corresponding point was computed for every point in corresponding linear. Finally, the average of the minimum Euclidean distance was regarded as distance of corresponding linear. In order to verify the validity of the method, this paper proposes two index of evaluation. One is average amplitude (F) for the stability of measurement, and the other is accuracy rate (R) for the accuracy of measurement. Contrast test of 4 distance measurement methods illustrated that the results of test are in accord with the characteristics of human cognition approximately.

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